The numbers of mapped single nevertheless reads from different experiments were 38,166,142 from the whole-eye technical replicates; 45,431,330 from the Wt whole eye; 66,643,381 from the Nrl?/? eye; 85,159,191 from the Wt retina; and 104,081,398 from the Nrl?/? retina. Technical replicates of the whole eye entailed running the sample library preparation on independent lanes on different day runs and analyzing them separately. Primary data transformation included image analysis, intensity scoring, base calling, and alignment, all carried out with Illumina pipeline software running on Linux. Image analysis identified distinct clusters and created digital intensity files describing the signal intensity of each cluster per cycle. Signal intensity profiles for each cluster were used to call bases, and quality scores for each base call were calculated for alignment.
Efficient Large-Scale Alignment of Nucleotide Databases (ELAND; Illumina) was then used for read mapping to the University of California�CSanta Cruz (UCSC; Santa Cruz, CA, USA) mouse genome assembly and transcript annotation (mm9) (45). For each read, ELAND determined the position in the genome to which the read substrings matched with a maximum of 2 errors. Base quality scores and the positions of the mismatches in a candidate alignment were used to calculate a probability score for each candidate, with the highest probability score indicating the best candidate. Eligible reads were defined by having a unique alignment to the genome or a single most probable alignment to the genome.
Other reads with failed quality control measures were not used in subsequent processing. The ELAND alignment was loaded onto Consensus Assessment of Sequence and Variation (CASAVA; Illumina) software for calculation of fragments per kilobase of exon model per million mapped reads (FPKM) statistics by gene, transcript, and exon. CASAVA counted the number of bases that belonged to exons and genes, and the numbers of bases that fell into the exonic regions of each gene were summed to obtain gene level counts. Normalized values were then calculated Drug_discovery as FPKM. The output for CASAVA was visualized with the GenomeStudio RNA Sequencing Module (Illumina), which allowed comparison between the samples based on the CASAVA output files. The raw files (fastq) and processed FPKM value data can be found online at the National Center for Biotechnology Information gene expression omnibus site with the series accession number “type”:”entrez-geo”,”attrs”:”text”:”GSE29752″,”term_id”:”29752″,”extlink”:”1″GSE29752 (http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=”type”:”entrez-geo”,”attrs”:”text”:”GSE29752″,”term_id”:”29752″GSE29752).